Evidence map›Paper›PMID 37815119›Full record

ArticleJournal of proteome research2023

Inclusion of Porous Graphitic Carbon Chromatography Yields Greater Protein Identification and Compartment and Process Coverage and Enables More Reflective Protein-Level Label-Free Quantitation.

Daniel G Delafield, Hannah N Miles, William A Ricke, Lingjun Li

Open access · greenAbstract read
In one paragraph

Article in Journal of proteome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 37% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Daniel G DelafieldDepartment of Chemistry, University of Wisconsin─Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States.
Hannah N MilesDivision of Pharmaceutical Sciences, University of Wisconsin─Madison, 777 Highland Avenue, Madison, Wisconsin 53075, United States.
William A RickeDivision of Pharmaceutical Sciences, University of Wisconsin─Madison, 777 Highland Avenue, Madison, Wisconsin 53075, United States.
Lingjun LiDepartment of Chemistry, University of Wisconsin─Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States.ORCID 0000-0003-0056-3869
University of Wisconsin–Madison · US

Funding

Role of Beta-Catenin in Urinary DysfunctionU54DK104310 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI BJORLING, DALE EDMOND · 2014 to 2023
$12.8M
Mass Spectrometric Studies of Neuropeptides in FeedingR01DK071801 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI LINGJUN LI · 2006 to 2026
$6.7M
Creating a region- specific biomolecular atlas of the brain of Alzheimer’s diseaseR01AG078794 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI LINGJUN LI, Luigi Puglielli · 2022 to 2026
$3.7M
Di-Leu-enabled multiplexed quantitation for biomarker discovery and validation in Alzheimer's diseaseRF1AG052324 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2018 to 2018
$2.4M
DiLeu-enabled multiplexed quantitation for biomarker discovery and validation in Alzheimer’s diseaseR01AG052324 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI LINGJUN LI · 2023 to 2026
$2.3M
Acquisition of a High-Field Dual Source FTICR-MS for Pharmaceutical ResearchS10RR029531 · NCRR · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2011 to 2011
$2.1M
Acquisition of a Dual-Source, High-Performance, Ion Mobility, Quadrupole Time-of-Flight Mass Spectrometry System for Biomedical Research at UW-MadisonS10OD028473 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2021 to 2021
$1.3M
Acquisition of a High Resolution High Speed MALDI Mass Spectrometer for Biomedical Research at UW-MadisonS10OD025084 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2018 to 2018
$598k
Probing Protein Structural Changes in Alzheimers DiseaseR21AG065728 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2020 to 2020
$420k
NCRR NIH HHS S10 RR029531NIA NIH HHS R01 AG052324NIA NIH HHS R01 AG078794NIA NIH HHS R21 AG065728NIA NIH HHS RF1 AG052324NIDDK NIH HHS R01 DK071801NIDDK NIH HHS U54 DK104310NIH HHS S10 OD025084NIH HHS S10 OD028473
6 · The paper itself

Abstract

The ubiquity of mass spectrometry-based bottom-up proteomic analyses as a component of biological investigation mandates the validation of methodologies that increase acquisition efficiency, improve sample coverage, and enhance profiling depth. Chromatographic separation is often ignored as an area of potential improvement, with most analyses relying on traditional reversed-phase liquid chromatography (RPLC); this consistent reliance on a single chromatographic paradigm fundamentally limits our view of the observable proteome. Herein, we build upon early reports and validate porous graphitic carbon chromatography (PGC) as a facile means to substantially enhance proteomic coverage without changes to sample preparation, instrument configuration, or acquisition methods. Analysis of offline fractionated cell line digests using both separations revealed an increase in peptide and protein identifications by 43% and 24%, respectively. Increased identifications provided more comprehensive coverage of cellular components and biological processes independent of protein abundance, highlighting the substantial quantity of proteomic information that may go undetected in standard analyses. We further utilize these data to reveal that label-free quantitative analyses using RPLC separations alone may not be reflective of actual protein constituency. Together, these data highlight the value and comprehension offered through PGC-MS proteomic analyses. RAW proteomic data have been uploaded to the MassIVE repository with the primary accession code MSV000091495.

Indexed as

CarbonGraphiteChromatography, Reverse-PhasePorosityProteomeProteomicsCarbonGraphiteProteomedata completenessLC-MSliquid chromatographymass spectrometryporous graphitic carbonproteomics

Identifiers

PMID37815119
PMCPMC10732698
OpenAlexW4387473265

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.